AI and the super app

uantumBlack, AI by McKinsey recently sat down with Selim Turki, head of data and AI at Careem, to discuss the latest trends in advanced analytics and artificial intelligence. Far from a dry discussion of theory, the conversation coalesced around several fascinating use cases in which Careem is using AI to make a difference in people’s lives. We discussed how AI is being leveraged to improve customer and driver security through targeted facial-recognition checks to ensure drivers (captains) are who they say they are. We also discussed how AI is being used to provide customers with the most accurate and up-to-date estimated times of arrival (ETAs) by factoring in a host of conditions, including local weather conditions, prayer times, and even iftar times during Ramadan. Along the way, we discussed what it means to be an “AI first” company and the outlook for AI tech—and talent—in the region.

QuantumBlack: Was AI always an important part of Careem’s growth journey? How has AI’s role evolved since Careem’s inception?

Selim Turki: We started our journey as a ride-hailing company booking journeys for corporate clients. We were initially booking cars manually, without a data server, before introducing more advanced systems to deliver more efficient, personalized experiences. Since day one, our mission has been to simplify and improve the lives of people—particularly our customers and captains. We quickly understood that maintaining high reliability for our dynamic marketplace 24/7 was a complex process that needed to be driven by instant decision making through continuous automation at scale.

We began processing real-time data, using algorithms and machine learning [ML] models to solve some of the core issues for our ride-hailing marketplace, including matching customers and captains efficiently, shaping our demand and supply via surge pricing, calculating accurate ETAs for our captains, and improving our maps and location search functionality

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Mots-clés : cybersécurité, sécurité informatique, protection des données, menaces cybernétiques, veille cyber, analyse de vulnérabilités, sécurité des réseaux, cyberattaques, conformité RGPD, NIS2, DORA, PCIDSS, DEVSECOPS, eSANTE, intelligence artificielle, IA en cybersécurité, apprentissage automatique, deep learning, algorithmes de sécurité, détection des anomalies, systèmes intelligents, automatisation de la sécurité, IA pour la prévention des cyberattaques.